基于ICEEMDAN与改进小波阈值的谐波检测方法

Harmonic Detection Method Based on ICEEMDAN with Improved Wavelet Thresholding

为了准确检测噪声环境下的电网谐波,提出改进小波阈值降噪和自适应噪声集合经验模态分解(ICEEMDAN)结合的谐波信号检测新方法。通过调节因子β调节阈值特性,并使用改进小波阈值进行降噪预处理;将去噪后的信号经ICEEMDAN分解,获取若干个内在模态分量(IMF),由相关系数判据去除虚假分量;最后通过希尔伯特变换(HT)解调出幅频信息。仿真实验表明:ICEEMDAN和改进的小波阈值方法结合,能够提高信噪比,并准确检测幅频信息和定位暂态信号的突变点。

In order to accurately detect power grid harmonics in noisy environments,a new method of harmonic signal detection is proposed by combining improved wavelet threshold noise reduction and improved complete ensemble empirical mode decomposition with adaptive noise(ICEEMDAN).The method first adjusts the threshold characteristics through the adjustment factorβ,and uses improved wavelet thresholding to pre-process the noise-containing harmonic signals for noise reduction.The processed signal is then decomposed by ICEEMDAN to obtain several intrinsic mode function(IMF)components,and the spurious components are removed by the correlation coefficient criterion.Finally the amplitude-frequency information is demodulated by the Hilbert transform(HT).Simulation experiments show that the combination of ICEEMDAN and the improved wavelet thresholding method can improve the signal-to-noise ratio and accurately detect the amplitude-frequency information as well as locate the mutation points of the transient signal.